aiqbench analysis
This software framework unifies quantum optics and structured light into a differentiable simulator, enabling AI-driven optimization for automated experimental design in physics. By leveraging JAX for hardware-accelerated automatic differentiation, it facilitates the search for new phenomena without relying on manual experiment configuration. This represents a significant convergence where machine learning techniques directly enhance the capabilities of quantum simulation tools.
esQueranto: Differentiable Structured Quantum Light for Automated Scientific Discovery
arXiv:2610.00750v1 Announce Type: new Abstract: Uncovering new phenomena in nature requires experiments. For centuries, their design has been exclusively a human endeavor. Today, a new paradigm is emerging in which artificial intelligence and computational methods can design experiments themselves. Realizing this form of automated scientific discovery requires simulators that are sufficiently expressive to represent the diverse physical processes and couplings from which new experiments can be constructed. In this direction, we introduce \textsc{esQueranto}, a differentiable software that brings photon-number quantum optics and structured-light propagation into a common description, allowing the spatial evolution of light to directly influence non-classical quantum states and their interference. \textsc{esQueranto} is implemented in JAX, providing automatic differentiation and hardware-accelerated evaluation for optimization and automated search. We demonstrate the framework across a broad range of quantum-optical applications that exercise complementary aspects of its physical description. By combining quantum and structured-light physics within a single differentiable simulator, \textsc{esQueranto} takes an important step towards the dream of a foundational simulator in physics.
Abstract:Uncovering new phenomena in nature requires experiments. For centuries, their design has been exclusively a human endeavor. Today, a new paradigm is emerging in which artificial intelligence and computational methods can design experiments themselves. Realizing this form of automated scientific discovery requires simulators that are sufficiently expressive to represent the diverse physical processes and couplings from which new experiments can be constructed. In this direction, we introduce \textsc{esQueranto}, a differentiable software that brings photon-number quantum optics and structured-light propagation into a common description, allowing the spatial evolution of light to directly influence non-classical quantum states and their interference. \textsc{esQueranto} is implemented in JAX, providing automatic differentiation and hardware-accelerated evaluation for optimization and automated search. We demonstrate the framework across a broad range of quantum-optical applications that exercise complementary aspects of its physical description. By combining quantum and structured-light physics within a single differentiable simulator, \textsc{esQueranto} takes an important step towards the dream of a foundational simulator in physics.
19 pages, 10 figures. Software and examples available at this https URL
arXiv:2610.00750 [quant-ph]
(or arXiv:2610.00750v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2610.00750 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 261 words
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